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Comparative Study to Predict Power Generation using Meteorological Information for Expansion of Photovoltaic Power Generation System for Railway Infrastructure

철도인프라용 태양광발전시스템 확대를 위한 기상정보 활용 발전량 예측 비교 연구

  • Yoo, Bok-Jong (Department of Electrical Engineering, Hanyang University) ;
  • Park, Chan-Bae (Department of Railroad Operation System Engineering, Korea National University of Transportation) ;
  • Lee, Ju (Department of Electrical Engineering, Hanyang University)
  • Received : 2017.07.26
  • Accepted : 2017.08.20
  • Published : 2017.08.31

Abstract

When designing photovoltaic power plants in Korea, the prediction of photovoltaic power generation at the design phase is carried out using PVSyst, PVWatts (Overseas power generation prediction software), and overseas weather data even if the test site is a domestic site. In this paper, for a comparative study to predict power generation using weather information, domestic photovoltaic power plants in two regions were selected as target sites. PVsyst, which is a commercial power generation forecasting program, was used to compare the accuracy between the predicted value of power generation (obtained using overseas weather information (Meteonorm 7.1, NASA-SSE)) and the predicted value of power generation obtained by the Korea Meteorological Administration (KMA). In addition, we have studied ways to improve the prediction of power generation through comparative analysis of meteorological data. Finally, we proposed a revised solar power generation prediction model that considers climatic factors by considering the actual generation amount.

Acknowledgement

Supported by : 한국연구재단

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